Identifying and tracking objects within a space poses several technical challenges. Existing systems use various image processing techniques to identify objects (e.g. people). For example, these systems may identify different features of a person that can be used to later identify the person in an image. This process is computationally intensive when the image includes several people. For example, to identify a person in an image of a busy environment, such as a store, would involve identifying everyone in the image and then comparing the features for a person against every person in the image. In addition to being computationally intensive, this process requires a significant amount of time which means that this process is not compatible with real-time applications such as video streams. This problem becomes intractable when trying to simultaneously identify and track multiple objects. In addition, existing system lacks the ability to determine a physical location for an object that is located within an image.